Safety quantification and optimization design method for wreckage landing area of carrier rocket

Abstract

The invention provides a carrier rocket wreckage landing area safety quantification and optimization design method, which comprises the following steps: establishing a passive stage carrier rocket wreckage flight dynamics model, and obtaining wreckage landing point distribution by adopting a polynomial chaos expansion method; fitting the distribution probability of the wreckage drop points of the carrier rocket by adopting a kernel density estimation method; according to population density distribution grids contained in the carrier rocket wreckage landing area, the probability that the carrier rocket wreckage falls in each grid area, the population number in each grid area, the equivalent effective casualty risk area of each grid area and the total area of each grid area, determining the number expectation of the number of landing area casualties; and judging the safety of the falling area according to whether the expected number of casualties in the falling area exceeds the safety threshold. The method solves the problem that the existing landing area safety assessment depends on traditional experience and is difficult to accurately quantify the landing area personnel casualty risk caused by the carrier rocket wreckage, and improves the landing area safety.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of launch vehicle trajectory design, and particularly relates to a launch vehicle debris impact area safety quantification evaluation and an impact area optimization design method based on the safety quantification evaluation result. BACKGROUND

[0002] With global high-density space launch, the launch vehicle impact area safety problem is increasingly prominent. In China, the population distribution is more extensive with economic development, and the original impact area surrounding population density has significantly increased, resulting in more severe impact area safety problem when performing space launch tasks. The traditional impact area safety design seriously depends on map operation and experience, mainly relies on impact area reconnaissance and qualitative analysis, and has not formed specific quantitative indicators for evaluating the impact area safety, so it is difficult to optimize the impact area safety design.

[0003] The present application breaks through the limitations of relying on traditional experience, and proposes an impact area safety evaluation and optimization design method based on the probability of quantifying personnel casualty risk. By considering the uncertain launch vehicle debris unpowered flight dynamics model, population distribution and personnel casualty model, the expected number of casualties in the impact area is calculated to quantitatively evaluate the debris impact area risk, and on this basis, an automatic generation method of the impact area personnel evacuation scheme with the least total number of evacuees when meeting the impact area safety requirements is proposed to guide the impact area safety optimization design. SUMMARY

[0004] In order to overcome the deficiencies in the prior art, the present application provides a launch vehicle debris impact area safety quantification and optimization design method, solves the problem that the existing impact area safety evaluation relies on traditional experience and is difficult to accurately quantify the personnel casualty risk of launch vehicle debris in the impact area, and improves the impact area safety. The launch vehicle debris impact point distribution under the condition of uncertainty is obtained based on the polynomial chaos expansion method to improve the calculation efficiency. The kernel density estimation method is used to fit the impact point distribution probability density function to improve the fitting accuracy of the long tail effect of the impact point distribution. Based on the dynamically updated population distribution data, an impact area safety quantification method with the expected number of casualties in the impact area as an index is formed.

[0005] The technical scheme provided by the present application is as follows:

[0006] In a first aspect, a launch vehicle debris impact area safety quantification and optimization design method comprises:

[0007] A passive stage launch vehicle debris flight dynamics model is established, and a polynomial chaos expansion method is used to obtain the debris impact point distribution;

[0008] A kernel density estimation method is used to fit the launch vehicle debris impact point distribution probability;

[0009] According to the population density distribution grid contained in the launch vehicle debris falling area, the probability of the launch vehicle debris falling in each grid area, the population number in each grid area, the equivalent effective casualty risk area of each grid area, and the total area of each grid area, the expected number of casualties in the falling area is determined.

[0010] According to whether the expected number of casualties in the falling area exceeds the safety threshold, it is judged whether the safety of the falling area meets the requirements, and if it does not meet the requirements and still needs to use the falling area, the expected number of casualties in the falling area is reduced through the personnel evacuation mode, so that the safety of the falling area meets the requirements.

[0011] In a second aspect, a launch vehicle debris falling area safety quantification and optimization design device comprises:

[0012] One or more processors;

[0013] A storage device for storing one or more programs,

[0014] When the one or more programs are executed by the one or more processors, the one or more processors implement the launch vehicle debris falling area safety quantification and optimization design method of the first aspect.

[0015] In a third aspect, a readable storage medium has a computer program stored thereon, which is executed by a processor to implement the launch vehicle debris falling area safety quantification and optimization design method of the first aspect.

[0016] In a fourth aspect, a computer program product comprises a computer program (also referred to as code or instructions), which, when executed, performs the launch vehicle debris falling area safety quantification and optimization design method of the first aspect.

[0017] The launch vehicle debris falling area safety quantification and optimization design method provided by the present application has the following beneficial effects:

[0018] (1) The present application proposes an evaluation method based on personnel casualty risk quantification for the problem of launch vehicle debris falling area safety evaluation, filling the domestic technical gap. This method can solve the problem of lack of quantitative indicators and dependence on traditional experience in existing falling area safety evaluation methods, and provides a scientific and quantitative basis for falling area safety design.

[0019] (2) The falling area safety evaluation method proposed in the present application uses a non-parametric kernel density estimation method, which can deal with various complex falling point distribution characteristics and has high evaluation accuracy. In addition, the polynomial chaos expansion method is used to replace the traditional Monte Carlo shooting method when predicting the falling point distribution, which greatly improves the calculation efficiency of safety evaluation.

[0020] (3) According to the quantitative result of the falling area safety, the application provides a personnel evacuation scheme automatic generation method for realizing the falling area safety requirement and minimizing the total number of evacuees, and designs a falling area safety design optimization scheme on the basis. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 A flow chart of the launch vehicle debris falling area safety quantification and optimization design method;

[0022] Figure 2 A global population density distribution map;

[0023] Figure 3 A personnel damage schematic diagram;

[0024] Figure 4 A personnel evacuation scheme generation method flow chart. DETAILED DESCRIPTION

[0025] The characteristics and advantages of the application will become more apparent with the following detailed description of the application.

[0026] Herein, the special word "exemplary" means "serving as an example, embodiment or illustration". Any embodiment described herein as "exemplary" is not necessarily to be construed as superior or better than the other embodiments.

[0027] The application provides a launch vehicle debris falling area safety quantification and optimization design method, constructs a "flight mechanics model-population distribution dynamic data-safety risk quantification method" quantitative analysis process, and converts the traditional falling area safety evaluation method based on experience into a falling area safety evaluation method based on risk probability quantification. First, a high-precision launch vehicle debris flight dynamics model is established in an uncertain environment to realize the falling point distribution prediction, and then the probability density function of the falling point distribution is obtained according to the probability statistical method; then, the personnel casualty risk heat map is constructed by superimposing the dynamically updated population spatio-temporal distribution data, the expected personnel casualty in the falling area is obtained as the falling area safety quantification index, and the falling area personnel evacuation scheme automatic generation method meeting the safety closed loop is proposed, and the falling area safety optimization design is carried out on the basis.

[0028] Reference Figure 1 , the launch vehicle debris falling area safety quantification and optimization design method specifically includes the following steps:

[0029] Step 1: Modeling of the launch vehicle debris passive stage considering uncertainty

[0030] A passive stage launch vehicle debris flight dynamics model is established in the launch coordinate system, as follows:

[0031]

[0032] where r is the position vector relative to the launch point in the launch coordinate system; v is the velocity vector in the launch coordinate system; m is the mass of the separated body; A is the aerodynamic force in the launch coordinate system; g is the gravitational acceleration in the launch coordinate system; a k and a e are the Coriolis acceleration and the coupled acceleration in the launch coordinate system, respectively.

[0033] The aerodynamic force A is usually expressed in the velocity system as drag D, lift L and side force S as follows:

[0034]

[0035] where drag D, lift L and side force S are expressed as:

[0036]

[0037] where: p is the atmospheric density; v air is the velocity of the launch vehicle debris relative to the atmosphere; S ref is the aerodynamic reference area; C d , C l and C s are the drag coefficient, the lift coefficient and the side force coefficient, respectively. Considering that the launch vehicle debris is usually in an uncontrolled state during the passive stage flight, and is also affected by the atmospheric wind field, accurate aerodynamic force calculation based on attitude is difficult to achieve, so constant aerodynamic force coefficients are used to represent the average effect of the passive stage aerodynamic force.

[0038] The gravitational acceleration g is calculated according to the ellipsoidal earth model as follows:

[0039]

[0040] where g rφr and are the components of the gravitational acceleration along the geocentric radial direction and the direction of the earth's rotational angular velocity, respectively; R 0 and are the unit direction vectors of the geocentric radial and the earth's rotational angular velocity, respectively.

[0041] Considering the J2 perturbation term of the ellipsoidal earth, g rφr and are expressed as follows:

[0042]

[0043] where p is the earth's gravitational coefficient; a E is the equatorial radius of the ellipsoidal earth; p is the geocentric latitude, and R is the geocentric distance.

[0044] The Coriolis acceleration ak The acceleration a is calculated according to the following formula:

[0045] a k = -2ω e ×v

[0046] The coupled acceleration a e can be calculated according to the following formula:

[0047] a e = -ω e ×(ω e ×R)

[0048] where ω e is the earth rotation angular velocity vector represented in the launch coordinate system; and R is the geocentric radius represented in the launch coordinate system.

[0049] Since the trajectory of the passive stage is affected by the comprehensive action of gravity and aerodynamic force, factors affecting the prediction accuracy of the falling point mainly include: the initial flight state accuracy of the passive stage, the atmospheric environment model accuracy and the aerodynamic model accuracy. In order to accurately describe the falling point distribution of the launch vehicle debris under the above uncertain factors, bias uncertainty modeling also needs to be performed.

[0050] The initial flight state of the passive stage is affected by factors such as active stage engine bias, structure bias, guidance shutdown and depletion shutdown, and finally shows that the position, velocity and mass bias of the separation point obey a certain random distribution. In the present application, the uncertainty of the initial position, velocity and mass of the passive stage is considered to be a normal distribution; the atmospheric environment mainly considers the atmospheric density bias, and is considered to be a uniform distribution; the bias of the passive stage aerodynamic model mainly considers the bias of the constant drag coefficient, lift coefficient and side force coefficient, and also obeys a uniform distribution. The various biases are shown in Table 1 as follows.

[0051] Table 1

[0052]

[0053] Through the above steps, after the uncertainty is randomly sampled, the falling point of the launch vehicle debris can be predicted by numerically integrating the dynamic equation, and the falling point longitude λ d and latitude φ d are obtained.

[0054] Second step: falling point prediction based on polynomial chaos expansion

[0055] Considering that the calculation efficiency of obtaining a large amount of falling point distribution data by using the traditional Monte Carlo shooting method is low, a polynomial chaos expansion (PCE) method is proposed to improve the efficiency of obtaining the falling point distribution data.

[0056] For a typical nonlinear stochastic dynamical system:

[0057]

[0058] where x is the stochastic state vector; t is time; ζ is a d-dimensional stochastic vector. The core idea of PCE method is to approximate the solution of stochastic dynamics with a series summation of orthogonal polynomial basis functions, as follows:

[0059]

[0060] where Φ i (ζ) is the tensor product of orthogonal polynomial basis functions; c i is the corresponding PCE coefficients; N is the summation term number, which is determined by the dimension d of stochastic vector and the orthogonal polynomial expansion order n:

[0061]

[0062] Since the distribution of each bias is assumed to be normal distribution and uniform distribution in the first step, Hermite polynomial and Legendre polynomial are used for expansion based on Askey scheme, respectively. By randomly sampling in the bias uncertainty space, M random vector samples ζ1, ζ2, …, ζ M are obtained, and the system response of M samples y(t, ζ1), y(t, ζ2), …, y(t, ζ M ) can be obtained by numerically integrating the passive segment dynamics equation, so as to construct the following linear equations:

[0063]

[0064] where the number of random samples M is not less than the number of PEC coefficients N to be solved. For convenience of representation, let the tensor product matrix of polynomial basis functions be A, the PCE coefficient vector be c, and the sample corresponding vector be y, so that the above overdetermined equations can be solved by least squares method to obtain the PCE coefficients:

[0065] c(t) = (A T A) -1 A T · y(t)

[0066] Through the above steps, the falling point distribution of the carrier rocket debris under uncertain environment can be predicted by a large number of samples with small calculation cost based on the polynomial chaos expansion method.

[0067] Step 3: Fitting of the probability density of the falling point distribution based on kernel density estimation

[0068] Considering that the distribution of launch vehicle debris drop points may have characteristics such as long tail and multi-peak, the traditional parametric fitting method based on multi-dimensional normal distribution cannot accurately evaluate the probability density, therefore, a non-parametric Kernel Density Estimation (KDE) method is used to fit the distribution of debris drop points.

[0069] KDE is a data-driven probability density estimation method, and its core idea is to place a symmetric kernel function K(·) at each sample point (x1, x2, …, xn), then superimpose all kernel functions and normalize to obtain a smooth density estimate. The specific expression is as follows: n

[0070]

[0071] Where p h (x) is the probability density estimate at x; n is the sample size; h is the bandwidth used to control the smoothness, which can be selected by the Silverman rule:

[0072]

[0073] Where, is the standard deviation of the sample.

[0074] Functions that meet the characteristics of non-negative, symmetric and integral 1 can be used as kernel functions. The present application uses Gaussian kernel for kernel density estimation, and its expression is:

[0075]

[0076] Where u is the value of the random sample point.

[0077] Through the above steps, the probability density function of special complex drop point distribution with characteristics such as long tail and multi-peak can be accurately fitted according to the kernel density estimation method.

[0078] Fourth step: combining population distribution data to quantify the safety of the drop area

[0079] The present application uses the latest LandScan 2023 global population density distribution data released by the United States Oak Ridge National Laboratory, which is shown in Figure 2 It divides the global area according to 1km×1km grid for statistics, forming global population distribution data, which can query the population density data in the corresponding grid according to the latitude and longitude information.

[0080] ​The present application considers the impact injury of the launch vehicle debris to the ground personnel, and establishes a more comprehensive and easy-to-implement personnel casualty model. For the personnel in the outdoor open area, the area where the launch vehicle debris may cause casualties to the personnel is divided into a core casualty risk area and an effective casualty risk area, as shown in Figure 3 .

[0081] The core casualty risk area is an area where the launch vehicle debris directly impacts the personnel to cause casualties, and the area A C can be calculated as follows:

[0082]

[0083] wherein r p is the radius of the core area of the human body; r f is the envelope radius of the separated body or its disintegrated fragments; h p is the height of the human body; and γ is the ballistic angle of the separated body or its disintegrated fragments impacting the ground.

[0084] Considering that in addition to direct impact, the launch vehicle debris may also cause secondary injuries such as projectile fragments due to disintegration caused by impact with the ground, the effective casualty risk area can be appropriately expanded on the basis of the core casualty risk area, and the area A E can be calculated as follows:

[0085] A E = K·A C

[0086] wherein K is an expansion coefficient, and K > 1.

[0087] Further considering that the population in an area is not all in the outdoor open area, and part of the personnel are in buildings or shelters of different protection levels, the possibility of their being impacted by the separated body is lower. In order to more accurately assess the personnel casualty risk, the present application places the personnel in the population distribution grid in buildings or shelters of different protection levels according to a certain proportion, and adopts the way of reducing the area of the effective casualty risk area to equivalent the protection of the buildings or shelters, as shown in Table 2 below.

[0088] Table 2

[0089]

[0090] After considering the protection of the buildings or shelters, the corresponding equivalent effective casualty risk area A e of the area can be calculated as follows:

[0091]

[0092] wherein j = 0, 1, 2, 3, 4.

[0093] When there are dynamic changes in population data, such as the implementation of population evacuation and other safety measures, dynamic change information can be directly accessed to adjust the number of people in the population distribution grid and the proportion of population in different protection levels, so as to obtain more realistic evaluation results.

[0094] The personnel casualty risk in a certain population distribution grid is considered, and the expected number of casualties in the grid area caused by the impact of the launch vehicle debris is To quantify the index, the following formula is used:

[0095]

[0096] Where P i represents the probability of the launch vehicle debris falling in the grid area; N i is the population in the grid area; is the equivalent effective casualty risk area of the grid area; A i is the total area of the grid area, and i is the grid number. Where N i and A i can be obtained from population distribution data, P i can be obtained according to the personnel casualty model, and P C needs to be based on the probability density function of the launch vehicle debris drop point distribution, and is obtained by integrating in the grid area:

[0097]

[0098] The sum of the expected number of casualties in each population grid is the quantitative index of the casualty risk of the population in the drop zone:

[0099]

[0100] Where E C represents the expected number of casualties in the drop zone caused by the launch vehicle debris.

[0101] Through the above steps, the safety of the drop zone can be quantified according to the expected number of casualties in the drop zone, and by comparing the quantitative evaluation results and safety indicators, it can be determined whether the safety of the drop zone meets the requirements.

[0102] Step 5: Optimization of drop zone safety design

[0103] If the expected number of casualties E C caused by the launch vehicle debris exceeds the safety threshold, the safety requirements cannot be met; at this time, if the drop zone still needs to be used, safety control measures such as population evacuation need to be taken to reduce E Cto the safety threshold. Under the premise of meeting the safety requirements, in order to minimize the size and cost of personnel evacuation, a safe evacuation scheme can be automatically generated based on the personnel casualty risk assessment results, so that the total number of evacuated people is minimized.

[0104] Referring to Figure 4 , the safe evacuation scheme generation method is as follows:

[0105] 1) Set the maximum casualty expectation E that meets the safety requirements C0 , if the currently evaluated casualty expectation E C is greater than E C0 , go to step 2); otherwise, the personnel evacuation scheme that meets the requirements has been obtained;

[0106] 2) Select the discrete population grid with the maximum casualty expectation, denoted as grid 1, the probability of the separation body falling into which is P1, and the corresponding casualty expectation is E C1 ; select the discrete population grid with the second largest casualty expectation, denoted as grid 2, the probability of the separation body falling into which is P2, and the corresponding casualty expectation is E C2 ; calculate the difference dE C between the casualty expectations of the two population grids = E C1 -E C2 ;

[0107] 3) Evacuate the population in grid 1 so that the casualty expectation is not greater than E C2 , the number of people needed to evacuate dN1 = ceil(dE C / P1), and record this evacuation data;

[0108] 4) Calculate the falling zone casualty expectation E C after evacuating dN1 people from grid 1, and return to step 1).

[0109] The above algorithm can ensure that each personnel evacuation is carried out along the maximum gradient of reducing the personnel casualty expectation, thereby obtaining the scheme with the least total number of evacuees.

[0110] On this basis, one or more candidate landing zones are demarcated around the landing zone corresponding to the original trajectory design, assuming that the distribution characteristics of the launch vehicle debris landing points remain unchanged, only translation is carried out in the candidate landing zone area, and the landing zone casualty expectation of the launch vehicle debris landing point distribution in each candidate landing zone is calculated through traversal, and the minimum total number of people evacuated to meet the safety index is calculated through personnel evacuation. Finally, the landing zone safety optimization design result with the optimal landing zone safety quantitative index of the launch vehicle debris landing zone and the minimum total number of people evacuated is obtained. The landing zone obtained by the safety optimization design is used as the landing zone constraint in the space launch task planning process, and the trajectory design parameters such as the firing direction, the shutdown time, the shutdown time trajectory inclination and the like are adjusted to realize the improvement of the safety of the debris landing zone. The above realizes the research on the quantitative evaluation and design optimization method of the safety of the launch vehicle debris landing zone.

[0111] The application further provides a launch vehicle debris landing zone safety quantification and optimization design device, comprising:

[0112] one or more processors;

[0113] a storage device for storing one or more programs,

[0114] When the one or more programs are executed by the one or more processors, the one or more processors implement the launch vehicle debris landing zone safety quantification and optimization design method of the first aspect.

[0115] The application further provides a readable storage medium having a computer program stored thereon, and the program is executed by a processor to implement the launch vehicle debris landing zone safety quantification and optimization design method of the first aspect.

[0116] The readable storage medium includes but is not limited to: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk and various program code storage media.

[0117] The application further provides a computer program product, which comprises: a computer program (also referred to as code or instructions), when the computer program is executed, the launch vehicle debris landing zone safety quantification and optimization design method of the first aspect is executed.

[0118] In the above embodiments, all or part can be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer readable storage medium or transferred from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions can be transferred from one website, computer, server or data center to another website, computer, server or data center through wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, microwave, etc.) mode.

[0119] Those skilled in the art can appreciate that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether the functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Skilled professionals can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0120] Those skilled in the art can clearly understand that, for the convenience and brevity of the description, the specific working processes of the devices, apparatuses and modules described above can refer to the corresponding processes in the foregoing method embodiments, which will not be described here.

[0121] The above describes the present application in detail in combination with specific embodiments and exemplary examples, but these descriptions cannot be understood as limitations of the present application. Those skilled in the art understand that various equivalent replacements, modifications or improvements can be made to the technical solutions and their embodiments of the present application without departing from the spirit and scope of the present application, which all fall within the scope of the present application. The scope of protection of the present application is subject to the appended claims.

[0122] The contents not described in detail in the specification of the present application are well known to those skilled in the art.

Claims

1. A method for quantifying and optimizing the safety design of launch vehicle debris landing zones, characterized in that, include: A flight dynamics model of the passive stage launch vehicle debris was established, and the debris impact point distribution was obtained by using a polynomial chaotic expansion method. The probability of launch vehicle debris impact point distribution is determined using the kernel density estimation method; Based on the population density distribution grid within the launch vehicle debris landing area, the probability of launch vehicle debris landing in each grid area, the population size in each grid area, the area of ​​the equivalent effective casualty risk zone in each grid area, and the total area of ​​each grid area, the expected number of casualties in the landing area is determined. Based on whether the expected number of casualties in the landing area exceeds the safety threshold, it is determined whether the landing area meets the safety requirements. If it does not meet the requirements but the landing area still needs to be used, the expected number of casualties in the landing area is reduced through the evacuation of personnel from the landing area, so that the landing area meets the safety requirements.

2. The method for quantifying and optimizing the safety design of the launch vehicle debris landing area according to claim 1, characterized in that, The steps for establishing the flight dynamics model of the passive-phase launch vehicle debris include: establishing the flight dynamics model of the passive-phase launch vehicle debris in the launch coordinate system, as follows: Where r is the position vector relative to the launch point in the launch coordinate system; v is the velocity vector relative to the ground in the launch coordinate system; m is the mass of the separated body; A is the aerodynamic force in the launch coordinate system; g is the gravitational acceleration in the launch coordinate system; a k and a e These are the Coriolis acceleration and the entrainment acceleration in the launch coordinate system, respectively; Aerodynamic force A is usually represented in the velocity system by drag D, lift L, and lateral force S as follows: The drag force D, lift force L, and lateral force S are represented as follows: In the formula: ρ is the atmospheric density; v air It is the velocity of the launch vehicle debris relative to the atmosphere; S ref It is the aerodynamic reference area; C d C l and C s These are the drag coefficient, lift coefficient, and lateral force coefficient, respectively.

3. The method for quantifying and optimizing the safety design of the launch vehicle debris landing area according to claim 2, characterized in that, In the step of obtaining the debris impact point distribution using the polynomial chaotic expansion method, the three parameters of the initial position of the passive segment, the initial velocity of the passive segment, and the initial mass of the passive segment follow a normal distribution, while the four parameters of atmospheric density, drag coefficient, lift coefficient, and lateral force coefficient follow a uniform distribution.

4. The method for quantifying and optimizing the safety design of the launch vehicle debris landing area according to claim 1, characterized in that, The expected number of casualties in the affected area is determined by the following formula: Among them, E C This is the expected number of casualties in the affected area; It is the expected number of casualties caused by the impact of launch vehicle debris in the i-th grid area; Among them, P i N is the probability that rocket debris will land in the i-th grid region; i It represents the population size in the i-th grid region; A is the area of ​​the equivalent effective casualty risk zone of the i-th grid region; i It is the total area of ​​the i-th grid region, where i is the grid number.

5. The method for quantifying and optimizing the safety design of the launch vehicle debris landing area according to claim 4, characterized in that, Considering that some personnel were in buildings or shelters with different protection levels when the launch vehicle debris impacted the area, determine the equivalent effective casualty risk zone area A of the grid region. e It is determined by the following formula: Where j is the protection level number, M j M is the proportion of the population covered by level j. j It is level j protection capability, A E It is the area of ​​the effective casualty risk zone.

6. The method for quantifying and optimizing the safety design of the launch vehicle debris landing area according to claim 5, characterized in that, The area A of the effective casualty risk zone E It is determined by the following formula: A E =K·A C Where, r p It is the radius of the core area of ​​the human body; r f h is the radius of the envelope of the separated body or its disintegrating fragments; p γ is the height of the human body; γ is the trajectory angle of the separated body or its fragments impacting the ground; K is the expansion coefficient, K>1.

7. The method for quantifying and optimizing the safety design of the launch vehicle debris landing area according to claim 1, characterized in that, The evacuation method for the affected area includes the following steps: (1) Set the expected maximum number of casualties E that meets safety requirements. C0 If the current assessment of the number of casualties in the landing area is expected to be E C Greater than E C0 Then proceed to step (2); otherwise, a satisfactory personnel evacuation plan has been obtained. (2) Select the discrete population grid with the highest expected number of casualties, denoted as grid 1. The probability of the isolated body falling into it is P1, and the corresponding expected number of casualties is E. C1 Choose the discrete population grid with the second largest expected number of casualties, denoted as grid 2. The probability P2 of the isolated object falling into it corresponds to the expected number of casualties E. C2 ; Calculate the difference dE between the expected number of casualties for two population grids. C =E C1 -E C2 ; (3) Evacuate the population in grid 1 to ensure that the expected casualties do not exceed E. C2 The number of people to be evacuated is dN1 = ceil(dE) C / P1), and record this evacuation data; (4) Calculate the expected number of casualties E in the landing area after evacuating dN1 people from grid 1. C (Return to step 1).

8. The method for quantifying and optimizing the safety design of the launch vehicle debris landing area according to claim 1, characterized in that, Also includes: Taking the original trajectory design-corresponding landing area as the center, at least one candidate landing area is delineated around it. Assuming that the distribution characteristics of the launch vehicle debris landing points remain unchanged, only the candidate landing area is translated. The expected number of casualties in each candidate landing area and the minimum total number of evacuees required to meet the safety indicators are determined by traversal. The area with the lowest expected number of casualties and the fewest total number of people to be evacuated is selected as the optimized area.

9. A device for quantifying and optimizing the safety design of launch vehicle debris landing areas, characterized in that, include: One or more processors; Storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the method for quantifying and optimizing the safety of launch vehicle debris landing areas as described in any one of claims 1 to 8.

10. A computer program product, characterized in that, The computer program product includes: a computer program that, when the computer program is run, executes the method for quantifying and optimizing the safety of the launch vehicle debris landing area as described in any one of claims 1 to 8.

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